Mercurial > repos > xuebing > sharplab_seq_motif
comparison mytools/cdf.r @ 0:39217fa39ff2
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author | xuebing |
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date | Tue, 13 Mar 2012 23:34:52 -0400 |
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-1:000000000000 | 0:39217fa39ff2 |
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1 # bin and average | |
2 binaverage = function(x,nbin,rankORvalue){ | |
3 # use x[,1] to bin x[,2] | |
4 binned = list() | |
5 if (rankORvalue == 'value'){ | |
6 mi = min(x[,1]) | |
7 ma = max(x[,1]) | |
8 bins = seq(mi,ma,length.out=nbin+1) | |
9 bins[1] = bins[1] - abs(mi)/100 | |
10 bins[nbin+1] = bins[nbin+1] + abs(ma)/100 | |
11 for (i in 1:nbin){ | |
12 binned[[i]] = x[x[,1] >= bins[i] & x[,1] < bins[i+1],2] | |
13 } | |
14 bins[1] = bins[1] + abs(mi)/100 | |
15 bins[nbin+1] = bins[nbin+1] - abs(ma)/100 | |
16 } else { | |
17 x = x[order(x[,1]),] | |
18 step = round(nrow(x)/nbin) | |
19 bins = x[1,1] | |
20 for (i in 1:(nbin-1)){ | |
21 binned[[i]] = x[((i-1)*step+1):(i*step),2] | |
22 bins = c(bins,x[i*step+1,1]) | |
23 } | |
24 binned[[nbin]] = x[((nbin-1)*step+1):nrow(x),2] | |
25 bins[nbin+1] = x[nrow(x),1] | |
26 } | |
27 # bin lavel | |
28 labels = character(0) | |
29 for (i in 1:nbin){ | |
30 labels = c(labels,paste(format(bins[i],digits=2,nsmall=2),format(bins[i+1],digits=2,nsmall=2),sep='~')) | |
31 } | |
32 list(binned=binned,bins=bins,labels=labels) | |
33 } | |
34 #res = binaverage(x,3,'rank') | |
35 | |
36 # CDF plot and KS.test | |
37 mycdf = function(list,title,labels,legendposition,xlabel,legend_title){ | |
38 L = length(list) | |
39 | |
40 # barplot for mean and std | |
41 avg = numeric(L) | |
42 err = numeric(L) | |
43 for (i in 1:L){ | |
44 avg[i] = mean(list[[i]]) | |
45 err[i] = sd(list[[i]]) | |
46 } | |
47 #print(list[[1]]) | |
48 #print(list[[2]]) | |
49 #print(avg) | |
50 #print(err) | |
51 par(cex=1.5,mar=c(8,6,6,4)) | |
52 xticks <- barplot(avg,names.arg=labels,las=2,ylab=xlabel,main='mean and standard deviation',xlab=legend_title,ylim=c(0,max(avg+err))) | |
53 arrows(xticks,avg+err, xticks, avg-err, angle=90, code=3, length=0.0) | |
54 | |
55 if (L>1){ | |
56 # ks test | |
57 cat('\nKS test:\n') | |
58 cat('sample1\tsample2\tp-value\n') | |
59 cat('-------------------------------------------------\n') | |
60 for (i in 1:(L-1)){ | |
61 for (j in (i+1):L){ | |
62 cat(labels[i],'\t',labels[j],'\t') | |
63 ks = ks.test(list[[i]],list[[j]]) | |
64 pv = max(2.2e-16,ks$p.value) | |
65 pv = format(pv,digits=3,nsmall=2) | |
66 cat(pv,'\n') | |
67 } | |
68 } | |
69 cat('-------------------------------------------------\n') | |
70 } | |
71 if (L == 2){ | |
72 title = paste(title,'\np=',pv,sep='') | |
73 } | |
74 # cdf plot | |
75 listx = list() | |
76 listy = list() | |
77 mi = 1e10 | |
78 ma = 1e-10 | |
79 for (i in 1:L){ | |
80 mi = min(mi,list[[i]]) | |
81 ma = max(ma,list[[i]]) | |
82 } | |
83 for (i in 1:L){ | |
84 listx[[i]] = c(mi,listx[i],ma) | |
85 listy[[i]] = c(0,listy[i],1) | |
86 } | |
87 for (i in 1:L){ | |
88 mi = min(mi,list[[i]]) | |
89 ma = max(ma,list[[i]]) | |
90 listx[[i]] = sort(list[[i]]) | |
91 listy[[i]] = c(1:length(list[[i]]))/length(list[[i]]) | |
92 } | |
93 #par(xlog=(xlog=='xlog')) | |
94 plot(listx[[1]],listy[[1]],type='l',lty=1,lwd=2,col=2,main=title,xlab=xlabel,ylab='cumulative frequency') | |
95 for (i in 2:L){ | |
96 lines(listx[[i]],listy[[i]],type='l',lty=i,lwd=2,col=i+1) | |
97 } | |
98 # legend | |
99 for (i in 1:L){ | |
100 labels[i] = paste(labels[i],', n=',length(list[[i]]),sep='') | |
101 } | |
102 legend(legendposition,legend=labels,col=2:(L+1), lty=1:L,lwd=2, bty='n',title=legend_title) | |
103 } |